Trained Model Weights and Dataset-Split Metadata for "Accelerating Radiative Transfer for Planetary Atmospheres by Orders of Magnitude with a Transformer-Based Machine Learning Model"

Trained model weights and dataset-provenance metadata accompanying the paper "Accelerating Radiative Transfer for Planetary Atmospheres by Orders of Magnitude with a Transformer-Based Machine Learning Model" (Malsky et al., submitted). Includes the trained transformer and LSTM model weights (best_model.pt, and the exported stand_alone_model.pt2 for the transformer), their training configurations/metadata/logs, the dataset-split indices (which PICASO-generated atmospheric profiles belong to the train/validation/test partitions), and the normalization statistics used to train the models. The data-generation pipeline (PICASO wrapper) and the emulator code are publicly available at https://github.com/imalsky/Problemulator.